Análisis exploratorio

Antonio Álvarez Caballero

11 de mayo de 2016

Columnas

##  [1] "Frame"                         "Minerals"                     
##  [3] "Gas"                           "Supply"                       
##  [5] "TotalMinerals"                 "TotalGas"                     
##  [7] "TotalSupply"                   "GroundUnitValue"              
##  [9] "BuildingValue"                 "AirUnitValue"                 
## [11] "AObservedEnemyGroundUnitValue" "AObservedEnemyBuildingValue"  
## [13] "AObservedEnemyAirUnitValue"    "EnemyMinerals"                
## [15] "EnemyGas"                      "EnemySupply"                  
## [17] "EnemyTotalMinerals"            "EnemyTotalGas"                
## [19] "EnemyTotalSupply"              "EnemyGroundUnitValue"         
## [21] "EnemyBuildingValue"            "EnemyAirUnitValue"            
## [23] "BObservedEnemyGroundUnitValue" "BObservedEnemyBuildingValue"  
## [25] "BObservedEnemyAirUnitValue"    "AObservedResourceValue"       
## [27] "BObservedResourceValue"        "Winner"
## [1] "El ganador es B"

Minerales

Minerales totales

Gas

Gas Total

Capacidad

Capacidad Total

GroundUnit

GroundUnit observada

Buildings

## [1] "Pendiente recta ganador: 0.489469915414255"
## [1] "Pendiente recta perdedor: 0.310893402183382"

Buildings observadas

AirUnits

AirUnits observadas

ResourceValue

Selección de características (No terminado)

## [0]  train-error:0.016802
## [1]  train-error:0.014987
## [2]  train-error:0.013198
## [3]  train-error:0.012272
## [4]  train-error:0.010910
## [5]  train-error:0.010431
## [6]  train-error:0.010012
## [7]  train-error:0.009730
## [8]  train-error:0.009525
## [9]  train-error:0.009302
## [10] train-error:0.009161
## [11] train-error:0.009127
## [12] train-error:0.008923
## [13] train-error:0.008678
## [14] train-error:0.008517
## [15] train-error:0.008438
## [16] train-error:0.008306
## [17] train-error:0.008328
## [18] train-error:0.008080
## [19] train-error:0.007861
## [20] train-error:0.007688
## [21] train-error:0.007497
## [22] train-error:0.007334
## [23] train-error:0.007283
## [24] train-error:0.007164
## [25] train-error:0.007094
## [26] train-error:0.007018
## [27] train-error:0.006899
## [28] train-error:0.006836
## [29] train-error:0.006728
## [30] train-error:0.006671
## [31] train-error:0.006633
## [32] train-error:0.006561
## [33] train-error:0.006504
## [34] train-error:0.006482
## [35] train-error:0.006355
## [36] train-error:0.006297
## [37] train-error:0.006194
## [38] train-error:0.006186
## [39] train-error:0.006180
## [40] train-error:0.006106
## [41] train-error:0.006043
## [42] train-error:0.006045
## [43] train-error:0.006023
## [44] train-error:0.005987
## [45] train-error:0.005983
## [46] train-error:0.005981
## [47] train-error:0.005977
## [48] train-error:0.005961
## [49] train-error:0.005955
## [50] train-error:0.005957
## [51] train-error:0.005953
## [52] train-error:0.005955
## [53] train-error:0.005957
## [54] train-error:0.005919
## [55] train-error:0.005919
## [56] train-error:0.005919
## [57] train-error:0.005919
## [58] train-error:0.005921
## [59] train-error:0.005923
## [60] train-error:0.005923
## [61] train-error:0.005919
## [62] train-error:0.005915
## [63] train-error:0.005907
## [64] train-error:0.005897
## [65] train-error:0.005889
## [66] train-error:0.005891
## [67] train-error:0.005889
## [68] train-error:0.005887
## [69] train-error:0.005880
## [70] train-error:0.005870
## [71] train-error:0.005870
## [72] train-error:0.005868
## [73] train-error:0.005866
## [74] train-error:0.005866
## [75] train-error:0.005868
## [76] train-error:0.005868
## [77] train-error:0.005870
## [78] train-error:0.005870
## [79] train-error:0.005870
## [80] train-error:0.005870
## [81] train-error:0.005874
## [82] train-error:0.005874
## [83] train-error:0.005874
## [84] train-error:0.005874
## [85] train-error:0.005874
## [86] train-error:0.005874
## [87] train-error:0.005874
## [88] train-error:0.005874
## [89] train-error:0.005876
## [90] train-error:0.005876
## [91] train-error:0.005822
## [92] train-error:0.005822
## [93] train-error:0.005822
## [94] train-error:0.005820
## [95] train-error:0.005822
## [96] train-error:0.005822
## [97] train-error:0.005822
## [98] train-error:0.005816
## [99] train-error:0.005818

Validación cruzada 5x2

## [0]  train-error:0.019852+0.000977   test-error:0.037193+0.001137
## [1]  train-error:0.016415+0.001793   test-error:0.033763+0.001267
## [2]  train-error:0.014221+0.000986   test-error:0.030842+0.000999
## [3]  train-error:0.012947+0.000817   test-error:0.028962+0.000809
## [4]  train-error:0.011955+0.000670   test-error:0.026720+0.000869
## [5]  train-error:0.011384+0.000715   test-error:0.025895+0.000850
## [6]  train-error:0.010888+0.000785   test-error:0.024737+0.000724
## [7]  train-error:0.010402+0.000753   test-error:0.023888+0.000693
## [8]  train-error:0.010106+0.000761   test-error:0.023272+0.000604
## [9]  train-error:0.009890+0.000823   test-error:0.022598+0.000509
## [10] train-error:0.009610+0.000841   test-error:0.022063+0.000492
## [11] train-error:0.009387+0.000887   test-error:0.021568+0.000470
## [12] train-error:0.009060+0.000872   test-error:0.021202+0.000454
## [13] train-error:0.008781+0.000785   test-error:0.020930+0.000424
## [14] train-error:0.008543+0.000707   test-error:0.020708+0.000410
## [15] train-error:0.008340+0.000591   test-error:0.020491+0.000405
## [16] train-error:0.008118+0.000545   test-error:0.020334+0.000254
## [17] train-error:0.007975+0.000519   test-error:0.020240+0.000182
## [18] train-error:0.007725+0.000418   test-error:0.020072+0.000220
## [19] train-error:0.007553+0.000403   test-error:0.019877+0.000166
## [20] train-error:0.007377+0.000368   test-error:0.019757+0.000147
## [21] train-error:0.007189+0.000325   test-error:0.019612+0.000237
## [22] train-error:0.007039+0.000322   test-error:0.019539+0.000216
## [23] train-error:0.006949+0.000287   test-error:0.019439+0.000243
## [24] train-error:0.006856+0.000258   test-error:0.019360+0.000225
## [25] train-error:0.006776+0.000264   test-error:0.019320+0.000175
## [26] train-error:0.006721+0.000256   test-error:0.019273+0.000195
## [27] train-error:0.006639+0.000258   test-error:0.019205+0.000179
## [28] train-error:0.006605+0.000259   test-error:0.019151+0.000125
## [29] train-error:0.006505+0.000234   test-error:0.019157+0.000152
## [30] train-error:0.006463+0.000239   test-error:0.019100+0.000173
## [31] train-error:0.006375+0.000201   test-error:0.019092+0.000199
## [32] train-error:0.006308+0.000221   test-error:0.019016+0.000228
## [33] train-error:0.006278+0.000220   test-error:0.018994+0.000275
## [34] train-error:0.006205+0.000239   test-error:0.018958+0.000219
## [35] train-error:0.006168+0.000240   test-error:0.018845+0.000213
## [36] train-error:0.006143+0.000258   test-error:0.018853+0.000253
## [37] train-error:0.006102+0.000232   test-error:0.018807+0.000286
## [38] train-error:0.006088+0.000229   test-error:0.018827+0.000313
## [39] train-error:0.006086+0.000234   test-error:0.018803+0.000343
## [40] train-error:0.006070+0.000243   test-error:0.018788+0.000333
## [41] train-error:0.006057+0.000245   test-error:0.018760+0.000357
## [42] train-error:0.006032+0.000226   test-error:0.018738+0.000328
## [43] train-error:0.006025+0.000225   test-error:0.018720+0.000327
## [44] train-error:0.005995+0.000224   test-error:0.018698+0.000301
## [45] train-error:0.005973+0.000208   test-error:0.018656+0.000315
## [46] train-error:0.005952+0.000208   test-error:0.018668+0.000334
## [47] train-error:0.005952+0.000213   test-error:0.018672+0.000328
## [48] train-error:0.005938+0.000197   test-error:0.018670+0.000317
## [49] train-error:0.005929+0.000198   test-error:0.018662+0.000343
## [50] train-error:0.005923+0.000203   test-error:0.018644+0.000342
## [51] train-error:0.005915+0.000204   test-error:0.018646+0.000339
## [52] train-error:0.005911+0.000200   test-error:0.018646+0.000324
## [53] train-error:0.005895+0.000203   test-error:0.018632+0.000312
## [54] train-error:0.005897+0.000202   test-error:0.018612+0.000311
## [55] train-error:0.005896+0.000202   test-error:0.018599+0.000319
## [56] train-error:0.005874+0.000203   test-error:0.018563+0.000296
## [57] train-error:0.005846+0.000180   test-error:0.018555+0.000287
## [58] train-error:0.005836+0.000196   test-error:0.018545+0.000268
## [59] train-error:0.005829+0.000192   test-error:0.018545+0.000275
## [60] train-error:0.005810+0.000223   test-error:0.018531+0.000292
## [61] train-error:0.005804+0.000232   test-error:0.018519+0.000281
## [62] train-error:0.005797+0.000222   test-error:0.018517+0.000277
## [63] train-error:0.005794+0.000220   test-error:0.018521+0.000278
## [64] train-error:0.005793+0.000221   test-error:0.018513+0.000279
## [65] train-error:0.005786+0.000217   test-error:0.018513+0.000271
## [66] train-error:0.005785+0.000217   test-error:0.018493+0.000260
## [67] train-error:0.005787+0.000217   test-error:0.018487+0.000263
## [68] train-error:0.005785+0.000212   test-error:0.018468+0.000263
## [69] train-error:0.005786+0.000213   test-error:0.018460+0.000248
## [70] train-error:0.005787+0.000214   test-error:0.018462+0.000254
## [71] train-error:0.005764+0.000256   test-error:0.018462+0.000260
## [72] train-error:0.005762+0.000256   test-error:0.018448+0.000258
## [73] train-error:0.005726+0.000245   test-error:0.018464+0.000258
## [74] train-error:0.005726+0.000245   test-error:0.018462+0.000251
## [75] train-error:0.005727+0.000245   test-error:0.018462+0.000250
## [76] train-error:0.005728+0.000246   test-error:0.018456+0.000254
## [77] train-error:0.005729+0.000246   test-error:0.018450+0.000256
## [78] train-error:0.005689+0.000217   test-error:0.018468+0.000247
## [79] train-error:0.005690+0.000217   test-error:0.018464+0.000242
## [80] train-error:0.005692+0.000217   test-error:0.018468+0.000243
## [81] train-error:0.005691+0.000218   test-error:0.018462+0.000242
## [82] train-error:0.005691+0.000218   test-error:0.018458+0.000240
## [83] train-error:0.005686+0.000211   test-error:0.018456+0.000248
## [84] train-error:0.005684+0.000213   test-error:0.018456+0.000248
## [85] train-error:0.005685+0.000213   test-error:0.018450+0.000247
## [86] train-error:0.005681+0.000211   test-error:0.018458+0.000246
## [87] train-error:0.005680+0.000210   test-error:0.018452+0.000245
## [88] train-error:0.005681+0.000211   test-error:0.018449+0.000242
## [89] train-error:0.005681+0.000211   test-error:0.018453+0.000247
## [90] train-error:0.005679+0.000208   test-error:0.018455+0.000245
## [91] train-error:0.005677+0.000207   test-error:0.018452+0.000244
## [92] train-error:0.005677+0.000207   test-error:0.018454+0.000246
## [93] train-error:0.005676+0.000203   test-error:0.018456+0.000228
## [94] train-error:0.005674+0.000202   test-error:0.018454+0.000226
## [95] train-error:0.005667+0.000202   test-error:0.018459+0.000221
## [96] train-error:0.005666+0.000204   test-error:0.018460+0.000225
## [97] train-error:0.005666+0.000204   test-error:0.018457+0.000222
## [98] train-error:0.005656+0.000206   test-error:0.018460+0.000230
## [99] train-error:0.005651+0.000201   test-error:0.018475+0.000214
##      train.error.mean train.error.std test.error.mean test.error.std
##   1:         0.019852        0.000977        0.037193       0.001137
##   2:         0.016415        0.001793        0.033763       0.001267
##   3:         0.014221        0.000986        0.030842       0.000999
##   4:         0.012947        0.000817        0.028962       0.000809
##   5:         0.011955        0.000670        0.026720       0.000869
##   6:         0.011384        0.000715        0.025895       0.000850
##   7:         0.010888        0.000785        0.024737       0.000724
##   8:         0.010402        0.000753        0.023888       0.000693
##   9:         0.010106        0.000761        0.023272       0.000604
##  10:         0.009890        0.000823        0.022598       0.000509
##  11:         0.009610        0.000841        0.022063       0.000492
##  12:         0.009387        0.000887        0.021568       0.000470
##  13:         0.009060        0.000872        0.021202       0.000454
##  14:         0.008781        0.000785        0.020930       0.000424
##  15:         0.008543        0.000707        0.020708       0.000410
##  16:         0.008340        0.000591        0.020491       0.000405
##  17:         0.008118        0.000545        0.020334       0.000254
##  18:         0.007975        0.000519        0.020240       0.000182
##  19:         0.007725        0.000418        0.020072       0.000220
##  20:         0.007553        0.000403        0.019877       0.000166
##  21:         0.007377        0.000368        0.019757       0.000147
##  22:         0.007189        0.000325        0.019612       0.000237
##  23:         0.007039        0.000322        0.019539       0.000216
##  24:         0.006949        0.000287        0.019439       0.000243
##  25:         0.006856        0.000258        0.019360       0.000225
##  26:         0.006776        0.000264        0.019320       0.000175
##  27:         0.006721        0.000256        0.019273       0.000195
##  28:         0.006639        0.000258        0.019205       0.000179
##  29:         0.006605        0.000259        0.019151       0.000125
##  30:         0.006505        0.000234        0.019157       0.000152
##  31:         0.006463        0.000239        0.019100       0.000173
##  32:         0.006375        0.000201        0.019092       0.000199
##  33:         0.006308        0.000221        0.019016       0.000228
##  34:         0.006278        0.000220        0.018994       0.000275
##  35:         0.006205        0.000239        0.018958       0.000219
##  36:         0.006168        0.000240        0.018845       0.000213
##  37:         0.006143        0.000258        0.018853       0.000253
##  38:         0.006102        0.000232        0.018807       0.000286
##  39:         0.006088        0.000229        0.018827       0.000313
##  40:         0.006086        0.000234        0.018803       0.000343
##  41:         0.006070        0.000243        0.018788       0.000333
##  42:         0.006057        0.000245        0.018760       0.000357
##  43:         0.006032        0.000226        0.018738       0.000328
##  44:         0.006025        0.000225        0.018720       0.000327
##  45:         0.005995        0.000224        0.018698       0.000301
##  46:         0.005973        0.000208        0.018656       0.000315
##  47:         0.005952        0.000208        0.018668       0.000334
##  48:         0.005952        0.000213        0.018672       0.000328
##  49:         0.005938        0.000197        0.018670       0.000317
##  50:         0.005929        0.000198        0.018662       0.000343
##  51:         0.005923        0.000203        0.018644       0.000342
##  52:         0.005915        0.000204        0.018646       0.000339
##  53:         0.005911        0.000200        0.018646       0.000324
##  54:         0.005895        0.000203        0.018632       0.000312
##  55:         0.005897        0.000202        0.018612       0.000311
##  56:         0.005896        0.000202        0.018599       0.000319
##  57:         0.005874        0.000203        0.018563       0.000296
##  58:         0.005846        0.000180        0.018555       0.000287
##  59:         0.005836        0.000196        0.018545       0.000268
##  60:         0.005829        0.000192        0.018545       0.000275
##  61:         0.005810        0.000223        0.018531       0.000292
##  62:         0.005804        0.000232        0.018519       0.000281
##  63:         0.005797        0.000222        0.018517       0.000277
##  64:         0.005794        0.000220        0.018521       0.000278
##  65:         0.005793        0.000221        0.018513       0.000279
##  66:         0.005786        0.000217        0.018513       0.000271
##  67:         0.005785        0.000217        0.018493       0.000260
##  68:         0.005787        0.000217        0.018487       0.000263
##  69:         0.005785        0.000212        0.018468       0.000263
##  70:         0.005786        0.000213        0.018460       0.000248
##  71:         0.005787        0.000214        0.018462       0.000254
##  72:         0.005764        0.000256        0.018462       0.000260
##  73:         0.005762        0.000256        0.018448       0.000258
##  74:         0.005726        0.000245        0.018464       0.000258
##  75:         0.005726        0.000245        0.018462       0.000251
##  76:         0.005727        0.000245        0.018462       0.000250
##  77:         0.005728        0.000246        0.018456       0.000254
##  78:         0.005729        0.000246        0.018450       0.000256
##  79:         0.005689        0.000217        0.018468       0.000247
##  80:         0.005690        0.000217        0.018464       0.000242
##  81:         0.005692        0.000217        0.018468       0.000243
##  82:         0.005691        0.000218        0.018462       0.000242
##  83:         0.005691        0.000218        0.018458       0.000240
##  84:         0.005686        0.000211        0.018456       0.000248
##  85:         0.005684        0.000213        0.018456       0.000248
##  86:         0.005685        0.000213        0.018450       0.000247
##  87:         0.005681        0.000211        0.018458       0.000246
##  88:         0.005680        0.000210        0.018452       0.000245
##  89:         0.005681        0.000211        0.018449       0.000242
##  90:         0.005681        0.000211        0.018453       0.000247
##  91:         0.005679        0.000208        0.018455       0.000245
##  92:         0.005677        0.000207        0.018452       0.000244
##  93:         0.005677        0.000207        0.018454       0.000246
##  94:         0.005676        0.000203        0.018456       0.000228
##  95:         0.005674        0.000202        0.018454       0.000226
##  96:         0.005667        0.000202        0.018459       0.000221
##  97:         0.005666        0.000204        0.018460       0.000225
##  98:         0.005666        0.000204        0.018457       0.000222
##  99:         0.005656        0.000206        0.018460       0.000230
## 100:         0.005651        0.000201        0.018475       0.000214
##      train.error.mean train.error.std test.error.mean test.error.std